Magnetic resonance method and apparatus to generate an image using a parallel acquisition technique

ABSTRACT

In a magnetic resonance method and apparatus to generate images by a parallel acquisition technique an excitation pulse is radiated into an examination subject, and a first echo train is generated after the excitation pulse, wherein the first echo train densely scans a segment of k-space to be scanned for an acquisition of coil calibration data. Coil calibration data are acquired by means of the first echo train. The acquired coil calibration data are stored in a coil calibration data set. A second echo train is generated after the same excitation pulse, wherein the second echo train undersamples a segment of k-space to be scanned for an acquisition of image data. Image data are acquired by means of the second echo train. The acquired image data are stored in an incomplete image data set. An image data set is generated by substituting data missing in the incomplete image data set due to the undersampling by means of a selected PAT reconstruction technique using the coil calibration data.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention concerns a method, a magnetic resonance apparatusand a computer program to generate images by means of a parallelacquisition technique.

2. Description of the Prior Art

Parallel acquisition techniques (PAT) enable the spatial frequency space(known as k-space) to be undersampled during a data acquisition (ameasurement) in magnetic resonance tomography (MRT), i.e. to fall belowthe density of the measured data points or data lines that is requiredaccording to the Nyquist theorem and to approximately calculate themissing data points (most often whole data lines) during the imagereconstruction or to directly suppress the aliasing artifacts resultingfrom the undersampling in the associated image space. The measurementtime that must be applied to acquire the raw data can thus be markedlyreduced. Furthermore, typical artifacts that occur given specialapplications or sequence techniques can be reduced in part with the aidof the parallel acquisition techniques. The requirement in order to beable to apply parallel acquisition techniques is multiple acquisitioncoils and the knowledge of the spatial sensitivities of the acquisitioncoils used in the acquisition of the raw data; this is also called aknowledge of the coil sensitivities. The coil sensitivities can becalculated approximately from what are known as coil calibration data.The coil calibration data are normally additionally measured. Thespatial information of the measurement data that is missing due to theundersampling is then compensated with the aid of the coil calibrationdata or with the use of the coil sensitivities of the acquisition coilsthat are calculated from the coil calibration data. The missing datapoints are thereby either substituted with the use of the coilcalibration data (or with the use of the coil sensitivities of theacquisition coils that are calculated from the coil calibration data)and the measured data points (measurement data), or the aliasingartifacts resulting from the undersampling are directly suppressed inimage space with the use of the coil sensitivities. In both cases thisis called a PAT reconstruction.

The coil sensitivities of the acquisition coils depend on, among otherthings, the orientation of the acquisition coils on the examinationsubject (for example a patient) and the respective load in the field,thus on properties of the examination subject at the location of theacquisition coil. The coil sensitivities therefore must be re-determinedat least for every examination subject. The sensitivity of theacquisition coils can also be affected during a measurement by movements(in particular macroscopic movements) of the examination subject, forexample breathing movements or other movements of a patient. The coilcalibration data are therefore ideally reacquired for every measurementand in close temporal proximity to the measurement data.

Different methods to measure the coil calibration data or, respectively,to determine the coil sensitivities are described in the article by M.Griswold et al., “Autocalibrated coil sensitivity estimation forparallel imaging”, M.R Biomed. 2006; 19: 316-324, for example.

However, the known methods to determine coil calibration data are notsuitable for every sequence technique for the data acquisition and/orare undesirably time-consuming.

SUMMARY OF THE INVENTION

An object of the invention is to provide a method, a magnetic resonanceapparatus and a computer-readable medium that enable amovement-insensitive and fast acquisition of coil calibration data forparallel acquisition techniques (PAT).

A method according to the invention to generate images by means ofparallel acquisition technique includes the steps of radiating anexcitation pulse into an examination subject, generating a first echotrain after the excitation pulse, wherein the first echo train denselyscans a segment of k-space to be scanned for an acquisition of coilcalibration data, acquiring coil calibration data by means of the firstecho train after the excitation pulse, storing the acquired coilcalibration data in a coil calibration data set, generating a secondecho train after the same excitation pulse, wherein the second echotrain undersamples a segment of k-space to be scanned for an acquisitionof image data, acquiring image data by means of the second echo trainafter the same excitation pulse, storing the acquired image data in anincomplete image data set, and generating an image data set bysubstituting data missing in the incomplete image data set due to theundersampling by means of a selected PAT reconstruction technique usingthe coil calibration data.

The invention is based on the following insights.

The autocalibration technique is a known method to determine coilcalibration data that is used especially frequently given changingmeasurement conditions. In this a portion of k-space (for the most partthe inner, central region) is scanned completely (also referred to as“densely”) corresponding to the aforementioned Nyquist theorem while theremainder of k-space (corresponding for the most part to the peripheralregion) is undersampled. The coil calibration data that are required forsubstitution of the undersampled regions are determined directly fromthe completely scanned region. The corresponding coil calibration dataare thus determined directly during each measurement. An additionaladvantage of the autocalibration technique is that the densely scannedregions require no substitution, and therefore the signal-to-noise ratio(SNR) in the acquired data is improved relative to completelyundersampled data.

However, the autocalibration technique is not suitable for all sequencetechniques, in particular not for the echoplanar sequences (EPIsequences). For example, if this autocalibration technique is used in asingle shot echoplanar sequence (single shot EPI), the coil calibrationdata and also the desired measurement data (most often image data) arethus acquired in a single echo train. This is possible in that themoment of the phase coding gradients (also designated as the “blip”)that is switched between the acquisition of two adjacent lines variesduring the echo train. For example, the moment of the phase codinggradients in the undersampled region (for example between two peripherallines that are acquired at the beginning and at the end of the echotrain) is greater by a factor of A than between two lines in the denselyscanned region (for example between two central lines). A is therebywhat is known as the acceleration factor. This variation in the speedwith which k-space is traversed along the phase coding direction duringthe echo train leads to smearing artifacts that make the quality of theacquired data unsatisfactory. Therefore the autocalibration technique isnot used for these sequence techniques (such as single shot EPI) inspite of its speed and movement insensitivity.

Another known method that is used in connection with EPI is theacquisition of the coil calibration data separate from the additionaldesired measurement data after one or more separate excitation pulses,for example in the course of a “prescan”.

If the coil calibration data are thereby read out in a “prescan” after asingle excitation, the phase coding gradient between the two adjacentlines of an EPI echo train that is used to acquire the image data has Atimes the moment of the phase coding gradient between two lines of anecho train that is used to acquire the coil calibration data.Accordingly, the speed along the phase coding direction during animaging echo train is greater by a factor of A than during an echo trainto acquire the coil calibration data. In echo planar imaging, the speedwith which k-space is traversed along the phase encoding directioncoincides with distortion or smearing artifacts. The different speedtherefore leads to different distortions between the acquired image dataand the coil sensitivities that can be determined from the coilcalibration data. These different distortions can have negative effectson the PAT reconstruction. Furthermore, the T₂* decay between theacquisition of two adjacent measured lines of the image data here isproportional to e^(−ES/T) ² *, while the T₂* decay between theacquisition of the corresponding lines in the coil calibration data setis proportional to e^(−A·ES/T) ² *. ES is thereby the temporal echospacing (ES), thus the time between successive echoes of the echo train.This also negatively affects the PAT reconstruction.

These two cited problems in the “prescan” method could be solved if the“prescans” are segmented, thus measured after multiple separateexcitations. The coil calibration data are thereby acquired segmentedusing A echo trains. The moment of the phase coding gradient between twoadjacent lines of the A echo trains to acquire the coil calibration dataand the moment of the phase coding gradient of the imaging echo trainare then equal. The speed along the phase coding direction and the T₂*decay between adjacent measured lines is therefore also equal. A phasecoding prephasing gradient at the beginning of the A echo trains toacquire the coil calibration data is thereby respectively chosen so thatthe data of the A echo cycles together densely scan k-space. However,this segmented method again has as a disadvantage relative to theacquisition of the coil calibration data after a single excitation thatmore time is required for the acquisition of the coil calibration data(A echo trains instead of a single echo train), and the sensitivity ofthe measurement relative to movements (for example of the patient) andother physiological effects (such as flow) is increased by thesegmentation.

Which method to use to determine the coil calibration data haspreviously depended on many factors, among other things on the PATreconstruction technique that is used, for example GRAPPA (“generalizedautocalibrating partially parallel acquisitions”), SMASH (“simultaneousacquisition of spatial harmonics”) or SENSE (“SENSitivity Encoding”)and/or the acceleration factor A.

In both cases, however, the time interval between the acquisition of thecoil calibration data and the acquisition of the image data or desiredmeasurement data, is at least a repetition time TR of the sequence thatis used. This repetition time TR is up to multiple seconds, for examplegiven diffusion-weighted imaging. This time interval is not negligiblecompared to the time constants associated with physiological movement ofthe examination organ (due to breathing, heart beat or peristaltic) andsuch can lead to inconsistencies between the acquired coil calibrationdata and the image data acquired with delay. These inconsistencies inturn negatively affect the quality of the parallel image reconstruction,for example in that they lead to an incomplete suppression of thealiasing artifacts resulting from the undersampling or to a degradationof the SNR.

This applies all the more in measurements in which an anatomical sliceis measured repeatedly, for example with the goal of improving the SNR.However, this is the rule in diffusion-weighted imaging, for example,wherein each slice is usually measured repeatedly, not only for SNRimprovement but also possibly with different alignment and/or amplitudeof an applied diffusion gradient. For effectiveness, particularly withregard to the necessary acquisition time, in diffusion-weighted imagingthe coil calibration data nevertheless have conventionally been mostoften acquired only once per slice and thereby normally with deactivateddiffusion gradients. The time interval between acquisition of the coilcalibration data and the image data thereby even amounts to multiple TRintervals.

With the method according to the invention, the acquisition of the coilcalibration data and the image data in two separate echo trains after acommon excitation pulse allows the time interval between thatacquisition of the coil calibration data and the image data to be keptsmall, in particular smaller than a repetition time TR of the datameasurement. Depending on the sequence technique that is used and thehardware that is used (in particular depending on the gradient system),the time interval between the acquisition of the coil calibration dataand the acquisition of the image data can be shortened to a few tenthsof milliseconds, so it is below the temporal time constants associatedwith the typical macroscopic movements of examination subjects such as(for example) breathing or heart beat of a patient. Therefore a robustparallel image reconstruction is possible under typical macroscopicmovements of the examination subject without the cited disadvantages ofthe known autocalibration techniques given special sequence techniques(such as EPI sequences).

The first echo train and/or the second echo train is/are advantageouslygenerated with an echoplanar imaging (EPI sequence). Echoplanar imagingis characterized by a particularly fast data acquisition and thusshortens the acquisition times for the respective data.

In another embodiment of the method, the coil calibration data set andthe imaging data are acquired in segmented fashion. A series ofexcitation pulses is radiated into the examination subject and, aftereach excitation pulse, one segment of the k-space to be acquired for theacquisition of the coil calibration data is acquired and one segment ofk-space to be acquired for the acquisition of image data is acquired.The amount of data of the two acquired data sets (consisting of thesuperimposed k-space segments) can be increased via such a segmentedacquisition with more excitation pulses (for example given an unchangedecho train length), and thus for example the resolution of thecalculated images can be improved. Furthermore, given such a segmentedacquisition of coil calibration data and image data the speed with whichk-space is traversed along the phase coding direction during the echotrain can be increased, and therefore distortion artifacts can bereduced.

In the embodiment just cited the first echo train and second echo trainare generated by an echoplanar imaging (EPI) sequence, wherein thedifferent segments are rotated relative to one another. A known sequencetechnique for this purpose is, for example, known as the PROPELLER EPI.A PROPELLER method in connection with parallel acquisition technique isdescribed in U.S. Pat. No. 7,482,806. However, due to the variablespeeds occurring there in the phase coding direction, this is notsuitable for EPI techniques for the aforementioned reasons.

In PROPELLER methods the parallel reconstruction ensues individually foreach segment (also called “blade”) before a superposition of the blades.By applying a method according to the invention with a PROPELLER EPItechnique, matching coil calibration data are acquired for each segmentof k-space that is scanned, and therefore for each orientation of thesegment. The time that is required for acquisition of the coilcalibration data can extend the echo time. In EPI sequences the echotime is the time interval between excitation pulse and acquisition ofthe central k-space line. However, this extension is usually small, forexample, in a diffusion weighted spin-echo EPI sequence, the timebetween excitation pulse and the first inversion pulse can normally notfully be used, for example, due to a desired symmetry of the diffusionmodule and a minimum number of lines that must be acquired before thecentral k-space line.

Therefore, in spite of acquisition of matching coil calibration data forevery scanned segment the method is particularly time-efficient sincecoil calibration data and image data can in fact be acquired by means oftwo echo trains, but after a common excitation pulse. In spite of thegeneration of a first echo train and a second echo train after thecommon excitation pulse the acquisition time for one blade does notnecessarily need to be extended since, for example, otherwise unusedfill times of the sequence that occur in some sequence techniques areused for the acquisition of the first echo train. Depending on thesequence technique that is used, however, under circumstances anextension of the time between two excitation pulses is necessary.However, the extension of the total measurement time that results inthis case is normally negligible relative to an extension of the totalmeasurement time as it arises given separate acquisition of coilcalibration data and image data.

In an advantageous embodiment of the method according to the invention,the first echo train and the second echo train are generated by anidentical sequence technique such that each echo train has a series ofechoes, with the time interval between successive echoes of the firstecho train being shorter than the time interval between successiveechoes of the second echo train. By shortening the echo spacing of thefirst echo train, the total measurement duration of the two acquisitionsis further reduced. Moreover, the speed along the phase coding directionin the two echo trains is simultaneously matched to one another, andtherefore the distortion artifacts in the respective data that werealready mentioned above are likewise matched to one another, forexample. The subsequent substitution with a PAT reconstruction techniqueis thus no longer negatively affected by inconsistencies in therespective distortions. The T₂* decay between the acquisition ofcorresponding k-space lines in the coil calibration data set and in theimage data set is likewise adapted, whereby the aforementioneddisadvantages are likewise avoided without (as in the prior art) havingto extend the measurement duration and increase the sensitivity tomovement and flow.

In addition to a sequence technique for EPI imaging, a sequencetechnique for turbo spin echo (TSE) imaging is also considered for thegeneration of the first echo train and second echo train.

The time interval between successive echoes of the first echo train isparticularly advantageously shortened by a factor of A relative to thetime interval of between successive echoes of the second echo train, andat the same time the spacing between lines scanned by means of the firstecho train in the segment of the k-space densely scanned for theacquisition of the coil calibration data is shortened by the same factorA relative to spacing of lines scanned by means of the second echo trainin the segment of k-space undersampled for the acquisition of the imagedata. In this way the adaptation of the speed along the phase codingdirections and the adaptation of the T₂* decay are optimized.

In another embodiment, artifacts in the incomplete image data set and/orin an image data set obtained from the incomplete image data set (bymeans of the parallel reconstruction technique) are corrected on thebasis of the coil calibration data set. Since the coil calibration dataof the coil calibration data set have been acquired by means of an echotrain completely scanning a segment of k-space, these data can be usedfor example to compare results of the reconstruction and/or for anaveraging of data present once in this way in the coil calibration dataset and once in the (possibly already substituted) incomplete image dataset, whereby the SNR can be further increased, for example.

A magnetic resonance apparatus according to the invention has multipleacquisition coils to acquire radio-frequency signals and a controlcomputer that is fashioned to implement the method described above.

A non-transitory computer-readable medium according to the invention isencoded with programming instructions to implement the method describedabove in a computer that operates a magnetic resonance apparatus whenthe programming instructions are executed in the computer.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 schematically illustrates a magnetic resonance apparatus operablein accordance with the invention.

FIG. 2 is a flowchart of an embodiment of the method according to theinvention.

FIG. 3 is a sequence diagram with which the method according to theinvention can be implemented.

FIGS. 4 and 5 show examples of trajectories in k-space that are scannedin the method according to the invention.

FIG. 6 is a flowchart of a basic PAT reconstruction.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

FIG. 1 schematically shows the basic components of a magnetic resonanceapparatus 1. In order to examine a body by means of magnetic resonanceimaging, various magnetic fields, that are matched to one another asprecisely as possible with regard to their temporal and spatialcharacteristics, are radiated into the body of a subject.

A strong magnet (typically a cryomagnet 5 with a tunnel-shaped opening)arranged in a radio-frequency-shielded measurement chamber 3 generates astatic, strong basic magnetic field 7 that is typically 0.2 Tesla to 7Tesla or more. An examination subject (for example a patient; not shownhere) to be examined is supported on a patient bed 9 and is positionedin the homogeneous region of the basic magnetic field 7.

Excitation of nuclear spins in the examination subject ensues by meansof radio-frequency excitation pulses that are radiated with at least oneradio-frequency antenna, for example a radio-frequency antenna shownhere as a body coil 13. The radio-frequency excitation pulses aregenerated by a pulse generation unit 17. After amplification by aradio-frequency amplifier 19, they are relayed to the at least oneradio-frequency antenna. The radio-frequency system shown here is onlyschematically indicated. Typically more than one pulse generation unit15, more than one radio-frequency amplifier 19 and multipleradio-frequency antennas are used in a magnetic resonance apparatus 1.

Furthermore, the magnetic resonance apparatus 1 has gradient coils 21with which magnetic gradient fields are radiated in a measurement (dataacquisition) for, among other things, selective slice excitation andspatial coding.

The gradient coils 21 are controlled by a gradient coil control unit 23that, like the pulse generation unit 15, is connected with the pulsesequence control unit 17.

The signals emitted by the excited nuclear spins are received by thebody coil 13 and/or local acquisition coils 25, amplified by associatedradio-frequency preamplifiers 27 and further processed and digitized bya receiver unit 29.

In the case of a coil that can be operated both in transmission mode andin acquisition mode (for example the body coil 13), the correct signalrelaying is regulated by an upstream transmission/reception diplexer 39.

A computer 37 that is connected with the magnetic resonance apparatusprocesses the measurement data. In particular, the computer 37implements a PAT reconstruction of received measurement data (forexample), wherein the computer 37 is connected with a memory unit 35such that the computer 37 can store results of the PAT reconstruction aswell as intermediate results of the processing of the measurement data,for instance (incomplete) image data sets or coil calibration data sets,in the memory unit 35 and also retrieve them again. Furthermore, thecomputer 37 can generate images from the measurement data (possiblyunder additional processing steps, for example corrections) that can bepresented to a user via an operator console 33 or be stored in thememory unit 35. The computer 37 furthermore controls the individualsystem components, in particular during the acquisition of themeasurement data. The computer 37 is fashioned so that the methodaccording to the invention can be implemented with it. For example, acomputer-readable medium 40 according to the invention is installed onthe computer 37 such that programming instructions encoded therein canbe executed, the programming instructions encoded in the computerprogram 40 thus implement a method according to the invention in thecomputer 37 when it is executed in the computer.

The shown units (in particular the computer 37 and the memory unit 35)are not necessarily to be understood as a physical unit; rather, theycan also be composed of multiple sub-units that are possibly arrangedphysically separately from one another.

FIG. 2 shows a flowchart of an embodiment of the method according to theinvention for the generation of image data sets by means of a parallelacquisition technique. An excitation pulse is radiated into anexamination subject in a first Step 101.

After the excitation pulse a first echo train is generated in a furtherStep 102. The first echo train hereby scans a segment of k-space to bedensely scanned for an acquisition of coil calibration data. The signalsgenerated in the examination subject by the first echo train areacquired as coil calibration data 105 and stored in a coil calibrationdata set 107.

In a further Step 104, a second echo train is likewise generated afterthe excitation pulse from Step 101. A segment of k-space to be scannedfor an acquisition of image data is hereby undersampled by the secondecho train. The signals generated in the examination subject by thesecond echo train are acquired as image data 106 and stored in anincomplete image data set 108.

Additional pulses or special gradient fields to prepare specific signalscan advantageously be switched (activated) between the first echo trainand the second echo train in Step 103. For example, at least oneinversion pulse can be switched to refocus phases of different spins inthe examination subject. Furthermore, in Step 103 it is possible toswitch at least one diffusion gradient between the first echo train andthe second echo train. For example, diffusion-weighted image data canthus be acquired.

In a last Step 109, an image data set is obtained from the incompleteimage data set in that data missing in the incomplete image data set aresubstituted using the coil calibration data set by means of a selectedPAT reconstruction technique. Possible PAT reconstruction techniquesare, for example, the aforementioned GRAPPA, SENSE or SMASH. Thepossible workflow of such a reconstruction is explained more preciselylater in connection with FIG. 6.

The image data set so obtained can be additionally processed, storedand/or displayed, as is generally indicated with regard to FIG. 1.

Steps 101 through 104 are possibly repeated for multiple segments ofk-space, as is indicated by the dashed arrow in FIG. 2. A series ofexcitation pulses is thus radiated into the examination subject, whereincoil calibration data sets 107 and incomplete image data sets 108 areacquired after each excitation pulse (thus for each segment) from whichin Step 109 at least one image data set is generated by means of theselected PAT reconstruction technique. If both coil calibration data andimage data are acquired by means of a first echo train and a second echotrain after each excitation pulse, the results of the PAT reconstructionare particularly reliable since the respective coil calibration datahave respectively been obtained in close temporal proximity to thecorresponding image data. Movement sensitivity of the method is thusreduced. Under the circumstances it is already sufficient if coilcalibration data and image data are only acquired after one (for examplethe first) excitation pulse in the manner described above, and onlyimage data are acquired after the remaining excitation pulses of theseries. Under the circumstances this increases the time efficiency butdegrades the movement insensitivity of the method.

FIG. 3 shows a schematic sequence diagram in the example of a basicsequence suitable for echoplanar imaging (EPI) with which a methodaccording to the invention can be advantageously implemented. The timesequence of radio-frequency pulses (time line RF), exemplaryslice-selection gradients (time line G_(S)), possible diffusiongradients (time line G_(D)) to be switched, exemplary phase codinggradients (time line G_(P)), possible readout gradients (time lineG_(R)) and the signal acquisition (time line ADC) is set with theaforementioned items in relation to one another in a conventionalmanner.

After an excitation pulse 201—for example a 90° pulse 90—a first echotrain 204 (signal not explicitly shown) is generated and acquired bymeans of a series of first readout gradients 203 and by means of aseries of first phase coding gradients 202. After the same excitationpulse 201, a second echo train 207 (signal not explicitly shown) isgenerated and acquired by means of a series of second readout gradients206 and by means of a series of second phase coding gradients 205. Thedata acquired via the readout are respectively stored as described abovein corresponding data sets, wherein coil calibration data are obtainedfrom the first echo train and incomplete image data are obtained fromthe second echo train. The series of first and second phase codinggradients 202, 205 is hereby respective depicted as a series of what areknown as “blips”.

The first echo train 204 thus scans k-space with sufficient densitywhile the second echo train 207 undersamples k-space. A sufficientlydense scan (sampling) can also be an oversampling according to theNyquist theorem, meaning that more data points than are necessaryaccording to the Nyquist theorem can also be measured.

At least one inversion pulse 208—for example a 180° pulse 180—can beswitched temporally between the first echo train 204 and second echotrain 207, and the second echo train can be acquired in a time window inwhich the peak of a spin echo also lies, which spin echo is generated bythe excitation pulse 201 and the at least one inversion pulse 208.Artifacts in the images—for example as a result of signal loss inregions with varying magnetic susceptibility or as a result ofinhomogeneities of the magnetic field—can thereby be reduced, inparticular when the central k-space lines of the incomplete image dataset are acquired in immediate proximity to the spin echo.

Furthermore, at least one diffusion gradient 209 can be switched betweenthe first echo train 204 and the second echo train 207 in order toacquire diffusion-weighted image data by means of the second echo train,which in this case is generated chronologically after the diffusiongradient 209. For the signal quality it is again advantageous to switchone or more inversion pulses 208 between the diffusion gradients 209. Ifthe coil calibration data 204 are obtained in this way before thediffusion gradients 209, they are not subject to the diffusion weightinggenerated by the diffusion gradients 209.

A time interval between acquisition of the coil calibration data and theimage data—thus a time interval between the first echo train and secondecho train—is hereby on the order of the a few tenths of a millisecond.An actual value of the time interval thereby depends on the desiredmaximum diffusion weighting of the acquired images that is normallyspecified as a b-value. The time that is required in order to achieve aspecified maximum diffusion weighting in turn depends on the gradientsystem of the installation magnetic resonance apparatus, in particularthe maximum gradient amplitude. The maximum gradient amplitude ofclinical MR tomographs is presently above 10 mT/m, and the maximumdesired diffusion weighting is normally around b=1000 s/mm². Under theseconditions, the time interval of the two echo trains is normallymarkedly below 100 ms. The lower limit of the time interval between thetwo echo trains given a small maximum diffusion weighting (b˜50 s/mm²)or without diffusion gradient is limited by the duration of the firstecho train and the duration of the inversion pulse. It can be specifiedwith 5 ms. The time interval thus lies in a range between 5 ms and 100ms and is therefore markedly shorter than the typical time constants ofthe human cardiac cycle (˜one second) and human breathing (3-10seconds). A particularly low movement sensitivity of the sequence isthus provided.

Furthermore, it is advantageous if additional navigator echoes 210 aregenerated with the first echo train and additional navigator echoes 211are generated with the second echo train, which navigator echoes 210,211 are acquired under readout gradients of the series 203 or,respectively, 206 and are respectively stored as navigator data.Navigator echoes are additional echoes that are generated and acquiredfor the purpose of artifact correction as it is explained in more detaillater. During the acquisition of the navigator data from the navigatorechoes 210 or, respectively, 211 the accumulated gradient moment in thephase coding direction is equal to zero. This can be achieved, forexample, by acquiring the navigator data at the beginning of therespective echo train and by activating each phase encoding prephasinggradient 202.1 and 205.1 after the acquisition of the respectivenavigator data, and with no phase coding gradient 202 or 205 beingactivated between the navigator echoes.

The acquired navigator data can be used to correct phase differencesbetween even and odd echoes of the respective associated echo train 204,207. Such phase differences can, for example, arise due to non-optimallybalanced gradient moments that, without correction, lead to artifacts,for instance to what are known as Nyquist ghosts or N/2 ghosts.

In the example shown in FIG. 3, the three first echoes are respectivelygenerated as navigator echoes 210, 211, acquired under the respectivefirst readout gradients of the series 203, 206 and respectively storedas sets of navigator data. The respective fourth echo is not acquiredsince a phase coding prephasing gradient 202.1, 205.1 is switchedparallel to this. The respective following echoes form the first or,respectively, second echo train in the sense of the method according tothe invention. After the phase coding prephasing gradient 202.1, 205.1,and after a series of phase coding gradients 202, 205, a phase codingrephasing gradient 202.2, 205.2 is advantageously respectively switchedhaving a moment that is set such that the accumulated moment of thephase coding prephasing gradient 202.1 and 205.1, all phase codinggradients of the series 202 and 205, and the phase coding rephasinggradient 202.2 and 202.5 are equal to zero.

An echo spacing ES1—thus a time interval between successive echoes andtherefore the time between the acquisition of immediately successivephase coding lines—of the first echo train 202 is thereby shorter than atime interval (echo spacing) ES2 between echoes of the second echotrain. In particular ES2=A*ES1 applies, for example, wherein A is theacceleration factor. It is particularly advantageous to simultaneouslyselect the moment of a phase coding gradient of the second series ofphase coding gradients 205 equal to A-times the moment of a phase codinggradient of the series 202. This results in a spacing d1 in k-space (seealso FIG. 4) of two k-space lines acquired during successive echoes ofthe first echo train being shorter by the acceleration factor A than aspacing dp2 in k-space (see FIG. 4) of two k-space lines acquired duringsuccessive echoes of the second echo train, such that it additionallyapplies that d2=A*d1.

The adaptation of the speed with which k-space is traversed along thephase coding direction and the adaptation of the T₂* decay are optimizedin this way. However, it is also possible forES2=A′*ES1 and d2=A*d1, with 1<A′<A

to apply for the echo spacing and the intervals line spacing.

This means that the echo spacing ES1 in the first echo train isshortened relative to the echo spacing ES2 in the second echo train byless than the acceleration factor A.

Possible k-space trajectories resulting from first and second echotrains generated in such a manner are shown as examples in FIGS. 4 and5. The dashed k-space trajectory 301, 301′ corresponds to the first echotrain and the dotted k-space trajectory 302, 302′ corresponds to thesecond echo train, wherein an acceleration factor A=2 was set in thedepictions of FIGS. 4 and 5. The distance between two adjacent linesthat are scanned during the first echo train is thus smaller by halfthan the distance between two adjacent lines that are scanned during thesecond echo train. As already mentioned above, the echo spacing of thefirst echo train is thereby ideally shorter by the aforementionedacceleration factor A than the echo spacing of the second echo train.For this purpose, it is accepted that the distance that the k-spacetrajectory 301 traverses along the readout direction (for example k_(x)in FIG. 4) during an echo is shorter than the distance that the k-spacetrajectory 302 traverses along the readout direction (for example k_(x)in FIG. 4) during an echo.

The segment of k-space that is scanned by the second echo trainadvantageously comprises the segment of k-space that is scanned by thefirst echo train. In particular if specific k-space points are scannedin this way with both the first and the second echo train, and thereforeare stored in both the coil calibration data set and the incompleteimage data set, artifacts in the incomplete image data set and/or in animage data set obtained from the incomplete image data set canadditionally be advantageously corrected on the basis of the coilcalibration data set.

FIG. 5 differs from FIG. 4 in that the k-space trajectories 301′ and302′ were rotated by an angle α in k-space relative to the k-spacetrajectories 301 an 302 from FIG. 4, as is typical in PROPELLERsequences, for example. A different segment of k-space than in FIG. 4 isthus scanned here.

Such k-space trajectories 301, 301′, 302, 302′ are also designed as“single propeller blades” (“blades”) in connection with PROPELLERsequence due to their shape. The scanning of different propeller bladeshereby occurs depending on an excitation pulse, as was already describedwith regard to FIG. 2, for example. For the acquisition of the completedata (thus all desired segments of k-space) the basic sequence depictedin FIG. 3 is thereby repeated for every segment, wherein the directionof the propeller blade (and therefore the direction of the applied phasecoding gradients and readout gradients) varies. For the acquisition of acomplete PROPELLER data set, the direction of the propeller blade ishereby successively rotated around the k-space center until all segmentstogether cover a circular region around the k-space center.

Even if a PROPELLER sequence is not used, the basic sequence shown inFIG. 3 can be repeated in the described manner, wherein for example themoment and/or the direction of possibly applied diffusion gradients isvaried in order to obtain different diffusion-weighted image data.

Diffusion-weighted (DW) imaging refers to the use of magnetic resonanceimaging techniques that exhibit diffusion properties of the examinedtissue. Diffusion is the Brownian movement of molecules in a medium. Insuch techniques the diffusion of water molecules upon the application ofa gradient field leads to a phase dispersion of the transversalmagnetization that leads to an attenuation of the acquired signal. Themagnitude of the signal attenuation depends on the duration andamplitude of the gradient field as well as on the type of tissue and itsmicrostructure.

The strong gradient fields that are used in diffusion-weighted imagingmake the techniques extremely sensitive to macroscopic movements (forexample patient movements) during the diffusion preparation (thus duringthe switching of diffusion gradients). The radio-frequency pulse pulsesand gradients of the basic sequence that primarily serve for thediffusion preparation of the transversal magnetization are frequentlyalso designated as a diffusion module, and the remaining gradients andpossible RF pulses that serve primarily to generate an echo train aredesignated as a readout module. Particularly fast image acquisitiontechniques can be used in order to avoid artifacts due to macroscopicmovements during the diffusion preparation. Among such particularly fastacquisition techniques are, for example, single shot EPI techniques thatallow a complete image to be acquired after a single excitation pulseand diffusion module. Artifacts that occur often given typical singleshot EPI techniques, for example distortions at susceptibilityboundaries, can be avoided or strongly reduced by the method describedabove since the speed with which k-space is traversed along the phaseencoding direction is increased by the undersampling during the secondecho train. At the same time, as already described above a movementsensitivity of the method is not increased as in PAT methods usuallyused in conjunction with EPI sequences. Therefore the method accordingto the invention is in particular suited for diffusion imaging with EPItechniques. Suitable EPI techniques include single shot EPI techniquesthat generate a first and/or second echo train that respectivelyencompass all of k-space to be scanned with the segment for therespective acquisition of coil calibration data or image data.

In tests a marked improvement of the image quality of diffusion-weightedimages of the brain of a test subject that were acquired with ashort-axis PROPELLER EPI sequence relative to a conventional short-axisPROPELLER EPI sequence without measures according to the invention couldbe demonstrated via use of the method according to the invention. Thefollowing parameters were thereby selected, for example:

Acceleration factor A=2; matrix size: 256; FOV (“field of view”): 230mm; TR=3000 ms; TE=73 ms; slice thickness: 4 mm; diffusion weighting,isotropic b=1000 s/mm²; readout length 64; 16 PROPELLER blades perimage; echo train length: 88 ms; echo spacing for the imaging echotrain: ES2=500 μs; echo spacing for the echo train with which coilcalibration data were acquired: ES1=250 μs.

In DW imaging with PROPELLER acquisition techniques it is conceivablethat coil calibration data are respectively acquired only once for eachorientation of the propeller blades (thus the segments), for examplegiven the least diffusion gradients and that these coil calibration dataare used in later for the substitution of incomplete image data whichwere acquired with the same orientation but different diffusiongradients. Although the time efficiency of the method is therebynormally additionally increased, losses in the movement insensitivitymust be accepted.

As an alternative to EPI techniques, the first echo train and secondecho train can also be generated otherwise, analogous to a sequencetechnique for turbo spin echo (TSE) imaging.

A flowchart for the implementation of a principle PAT reconstruction asit can be used in Step 109 from FIG. 2 is schematically shown in FIG. 6.

A densely (or sufficiently) scanned (sampled) coil calibration data set401—for example the coil calibration data set 107 from FIG. 2—and anundersampled (and therefore incomplete) image data set 404—for examplethe incomplete image data set 108 from FIG. 2—are hereby advantageouslyprepared first for the substitution (Steps 402 and 405).

The preparation 402 of the coil calibration data set 401 and/or thepreparation 405 of the incomplete image data set 404 can includemirroring 402.1, 405.1 of every second k-space line at the origin in thereadout direction if the direction of the associated k-spacetrajector(y/ies) alternates in successive echoes in the readoutdirection (k_(x) direction in FIG. 4) as in an EPI k-space trajectory.The data are thus “aligned”, so to speak, which facilitates theadditional processing.

Furthermore, the preparation 402 of the coil calibration data set 401and/or the preparation 405 of the incomplete image data set 404 caninclude an interpolation 4022, 405.2 to a Cartesian grid (“readoutregridding”). A varying interval in k-space between data points acquiredwith constant time interval, possibly due to a non-ideal readoutgradient, is hereby compensated. The individual data points areaccordingly arranged on a Cartesian grid, which normally drasticallysimplifies the further processing steps. In particular, particularlyefficient algorithms such as the fast Fourier transformation cantherefore be used. Such non-ideal readout gradients arise given EPIsequences, for example, if the data acquisition starts before reaching aplateau of a trapezoidal readout gradient. Such a data acquisition, alsocalled “ramp sampling”, is used to minimize the echo spacing of the EPIsequence that is thereby possible, for example. A short echo spacing inturn increases the speed with which the k-space trajectory is traversedalong the phase coding direction.

If navigator data associated with the coil calibration data set 401and/or the incomplete image data set 404 are also present, for examplevia an acquisition of navigator data as it can ensue in the basicsequence described with regard to FIG. 3, it is furthermore possiblethat the preparation 402 of the coil calibration data set 401 and/or thepreparation 405 of the incomplete image data set 404 includes acorrection 402.3, 405.3 of phase inconsistencies between even and oddechoes of an echo train by means of which the coil calibration data set401 was acquired, or between even and odd echoes of an echo train bymeans of which the incomplete image data set 404 was acquired. The citedphase inconsistencies can be detected from the navigator data and thencan be corrected for the following echoes of the echo train. Forexample, Nyquist ghost artifacts in images that are calculated from thecoil calibration data set 401 or, respectively, the incomplete imagedata set 404 can thereby be avoided or, respectively, at least reduced.

The order in which the cited preparation steps 402.1, 402.2, 402.3 and405.1, 405.2, 405.3 are shown in FIG. 6 if they are all included in therespective preparations 402 and 405 is only an example.

In a next Step 403 factors (for example) are calculated from the(possibly prepared) sufficiently scanned coil calibration data set, bymeans of which the data missing in the undersampled, incomplete imagedata set are substituted in a further Step 406.

This is explained in the following in the example of a GRAPPA PATreconstruction.

In GRAPPA the signal s_(i)({right arrow over (k)}) of every missingk-space point {right arrow over (k)} (which is missing because it is notscanned due to the undersampling) is expressed as a linear combinationof the measured (thus scanned) points adjacent to this point {rightarrow over (k)}:

${{s_{i}\left( \overset{\rightarrow}{k} \right)} = {\sum\limits_{j = 1}^{N_{C}}{\sum\limits_{\overset{\rightarrow}{q} \in \Omega}{{n_{i,\overset{\rightarrow}{k}}\left( {j,\overset{\rightarrow}{q}} \right)}{s_{j}\left( \overset{\rightarrow}{q} \right)}}}}};$with i=1, . . . , N_(C) and n_(i,{right arrow over (k)}) as linearfactors (what are known as “GRAPPA weights”), wherein the first sumcounts the acquisition coils (thus N_(C) is equal to the number ofparticipating acquisition coils of the magnetic resonance apparatus),the second sum counts all data points measured in a neighborhoodΩ_({right arrow over (k)}) of {right arrow over (k)}, and s_(j)({rightarrow over (q)}) represents the measured signal of the acquisition coilj at the sample point {right arrow over (q)}. Given Cartesian scanning,the linear factors are hereby independent of {right arrow over(k)}=(k_(x),k_(y)) and can therefore be calculated from those data ofthe coil calibration data set for which the s_(i)({right arrow over(k)}) values on the left side of the above equation system are known.

In GRAPPA the factors n_(i,{right arrow over (k)}) for the substitutionare thus calculated in Step 403, for example via a pseudo-inversion ofthe above equation system. In Step 406 the data missing in theincomplete image data set are subsequently calculated by inserting thecalculated factors n_(i,{right arrow over (k)}) into the above equationsystem.

Instead of GRAPPA, another known PAT reconstruction method can also beused, for example SMASH or SENSE.

In Step 406 the undersampled (and therefore incomplete) image data set404 is thus supplemented by means of the data calculated in Step 403 andsubjected to possible additional known corrections (depending on thesequence technique used for the data acquisition) and/or processingsteps in order to obtain an image data set 407. For example, if a singleshot ER sequence technique is used for the data acquisition of theincomplete image data set, a two-dimensional, discrete Fouriertransformation can already be sufficient as an additional processingstep in order to obtain the image data set. Additional corrections canbe implemented on the basis of the coil calibration data set, forexample, in that a comparison of signals of k-space points that werescanned both in the coil calibration data set 401 and in the incompleteimage data set 404 is implemented, for example.

Although modifications and changes may be suggested by those skilled inthe art, it is the intention of the inventor to embody within the patentwarranted hereon all changes and modifications as reasonably andproperly come within the scope of his contribution to the art.

I claim as my invention:
 1. A method to generate magnetic resonanceimage data sets using a parallel acquisition technique, comprising thesteps of: generating a first echo train after radiating an excitationpulse into an examination subject; said first echo train sufficientlydensely scanning a segment of k-space to be scanned for an acquisitionof coil calibration data; acquiring said coil calibration data from saidfirst echo train after said excitation pulse; electronically storing theacquired coil calibration data in a coil calibration data set;generating a second echo train after said excitation pulse with no otherexcitation pulse intervening between said excitation pulse and saidsecond echo train, said second echo train undersampling, according tothe Nyquist theorem, a segment of k-space to be scanned for anacquisition of image data; acquiring said image data from said secondecho train after said excitation pulse; electronically storing theacquired image data in an incomplete image data set, in which data aremissing due to said undersampling; and reconstructing data, asreconstructed data, using a selected parallel acquisition reconstructiontechnique and using said coil calibration data, and generating acomplete image data set by substituting said reconstructed data for saiddata that are missing in the incomplete image data set due to theundersampling.
 2. A method as claimed in claim 1 comprising generatingsaid first and second echo trains using an echo planar imaging sequence.3. A method as claimed in claim 1 comprising generating said first andsecond echo trains with a sequence wherein said segment of k-spacescanned for the acquisition of coil calibration data and said segment ofk-space scanned for the acquisition of said image data each comprise anentirety of k-space.
 4. A method as claimed in claim 3 comprisinggenerating said first and second echo trains with a single shot echoplanar imaging sequence.
 5. A method as claimed in claim 1 comprisingactivating at least one inversion pulse between said first echo trainand said echo train.
 6. A method as claimed in claim 1 comprisingactivating at least one diffusion gradient between said first echo trainand said second echo train.
 7. A method as claimed in claim 6 comprisinggenerating said first echo train chronically before activating said atleast one diffusion gradient.
 8. A method as claimed in claim 1comprising radiating a series of excitation pulses into the examinationsubject and scanning respectively different segments of k-space afterthe respective excitation pulses for the acquisition of said coilcalibration data and for the acquisition of said image data.
 9. A methodas claimed in claim 8 comprising generating said first and second echotrains using a PROPELLER echo planar imaging sequence with saidrespective segments of k-space scanned for acquisition of said coilcalibration data and scanned for said acquisition of said image databeing scanned by rotating a PROPELLER blade.
 10. A method as claimed inclaim 9 comprising generating said first and second echo trains using anecho planar imaging sequence.
 11. A method as claimed in claim 1comprising generating said first and second echo trains with anidentical sequence technique such that the time interval betweensuccessive echoes of said first echo train to be shorter by a factor ofA than the time interval between successive echoes of said second echotrain, and scanning said segment of k-space for the acquisition of saidcoil calibration data with an interval between k-space lines that isshorter by said factor A than an interval of k-space lines scanned bysaid second echo train in the segment of k-space that is undersampledfor the acquisition of said image data.
 12. A method as claimed in claim1 comprising generating said first and second echo trains with a turbospin echo imaging sequence.
 13. A method as claimed in claim 1comprising scanning a segment of k-space with said second echo trainthat contains the k-space segment that was scanned with said first echotrain.
 14. A method as claimed in claim 1 comprising correctingartifacts in at least one of said incomplete image data set and saidimage data set using said coil calibration data set.
 15. A magneticresonance apparatus to generate magnetic resonance image data sets usinga parallel acquisition technique, comprising: a magnetic resonance dataacquisition units: a control unit configured to operate said dataacquisition unit to radiate an excitation pulse into an examinationsubject and to generate a first echo train after said excitation pulse,said first echo train sufficiently densely scanning a segment of k-spaceto be scanned for an acquisition of coil calibration data, and toacquire said coil calibration data from said first echo train after saidexcitation pulse; a memory; said control unit being configured to storethe acquired coil calibration data in a coil calibration data set insaid memory; said control unit being configured to operate said dataacquisition unit to generate a second echo train after said excitationpulse with no other excitation pulse intervening between said excitationpulse and said second echo train, said second echo train undersampling,according to the Nyquist theorem, a segment of k-space to be scanned foran acquisition of image data, and to acquire said image data from saidsecond echo train after said excitation pulse; said control unit beingconfigured to store the acquired image data in an incomplete image dataset, in which data are missing due to said undersampling; and an imagecomputer having access to said memory and configured reconstructingdata, as reconstructed data, using a selected parallel acquisitionreconstruction technique and using said coil calibration data, and togenerate a complete image data set by substituting said reconstructeddata for said data that are missing in the incomplete image data set dueto the undersampling.
 16. A non-transitory computer-readable mediumencoded with programming instructions, said medium being loaded into acomputer system of a magnetic resonance apparatus, comprising a magneticresonance data acquisition unit, and said programming instructionscausing said computer system to: operate said data acquisition unit toradiate an excitation pulse into an examination subject and to generatea first echo train after said excitation pulse, said first echo trainsufficiently densely scanning a segment of k-space to be scanned for anacquisition of coil calibration data, and to acquire said coilcalibration data from said first echo train; electronically store theacquired coil calibration data in a coil calibration data set; operatethe data acquisition unit to generate a second echo train after saidexcitation pulse with no other excitation pulse intervening between saidexcitation pulse and said second echo train, said second echo trainundersampling, according to the Nyquist theorem, a segment of k-space tobe scanned for an acquisition of image data, and to acquire said imagedata from said second echo train; electronically store the acquiredimage data in an incomplete image data set, in which data are missingdue to said undersampling; and reconstructing data, as reconstructeddata, using a selected parallel acquisition reconstruction technique andusing said coil calibration data, and generate a complete image data setby substituting said reconstructed data for said data that are missingin the incomplete image data set due to the undersampling.